Automated moving platform

ABSTRACT

This disclosure describes systems and methods used in the development and validation of autonomous vehicles ability to track objects with sensors. This application describes a self-propelled autonomous platform and methods for carrying a pedestrian, cyclist or vehicular type target in a predetermined pattern during one or more testing runs. The self-propelled autonomous platform includes a sensor configured to retract within a platform housing of the self-propelled autonomous platform when being driven over during a test run.

FIELD

This description relates to a self-propelled autonomous platform and, insome embodiments, to a self-propelled autonomous platform configured tocarry a target to test the performance of at least one autonomousvehicles.

BACKGROUND

Autonomous vehicles can be used to transport people and/or cargo (e.g.,packages, objects, or other items) from one location to another. Forexample, an autonomous vehicle can navigate to the location of a person,wait for the person to board the autonomous vehicle, and navigate to aspecified destination (e.g., a location selected by the person). Tonavigate in the environment, these autonomous vehicles are equipped withvarious types of sensors to detect objects in the surroundings.

SUMMARY

Anticipating the behavior of objects using the sensors of an autonomousvehicle can be difficult. The present disclosure is directed to systems,methods, and computer program products for developing and validating theability of the autonomous vehicle to track objects with the sensors.This application describes a self-propelled autonomous platform andmethods for carrying an object representing a pedestrian, cyclist orvehicle during one or more testing runs. In some embodiments, the one ormore testing runs can include carrying (e.g., moving) the object in apredetermined pattern. The carriage of these targets in thepredetermined pattern or patterns allows the autonomous vehicle toconduct tests to determine how accurately the sensors are able to detectand predict the behavior of objects in an environment surrounding anautonomous vehicle. Generally, the computer system is configured toreceive input from one or more sensors of the vehicle, detect one ormore objects in the environment surrounding the vehicle based on thereceived input, and operate the vehicle based upon the predictedbehavior of the objects.

In some embodiments, a self-propelled platform includes a plurality ofwheels; a motor configured to drive at least one of the plurality ofwheels; a platform housing comprising a support surface configured tocarry at least one target and a sloped periphery configured toaccommodate passage of an autonomous vehicle over the platform housing;and a suspension comprising a plurality of springs coupling theplurality of wheels to the platform housing, the plurality of springsconfigured to transition the platform from a first state to a secondstate in response to a threshold amount of weight being applied to theplatform housing, wherein the platform housing is lower in the secondstate than it is in the first state.

In some embodiments, provided is a self-propelled platform, including asensor; at least one processing circuit; a wireless communicationmodule; and at least one non-transitory storage media storinginstructions which, when executed by the at least one processingcircuit, cause performance of operations including: following a firstmovement route in accordance with a user input; recording a plurality ofpositions of the self-propelled platform based on data collected by thesensor while following the first movement route; and following a secondmovement route based on the plurality of positions in response to anautonomous vehicle arriving at a predetermined position.

These and other aspects, features, and implementations can be expressedas methods, apparatuses, systems, components, program products, means orsteps for performing a function, and in other ways.

These and other aspects, features, and implementations will becomeapparent from the following descriptions, including the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows an example of an autonomous vehicle having autonomouscapability.

FIG. 2 illustrates an example “cloud” computing environment.

FIG. 3 illustrates a computer system.

FIG. 4 shows an example architecture for an autonomous vehicle.

FIG. 5 shows an example of inputs and outputs that may be used by aperception module.

FIG. 6 shows an example of a LiDAR system.

FIG. 7 shows the LiDAR system in operation.

FIG. 8 shows the operation of the LiDAR system in additional detail.

FIG. 9 shows a block diagram of the inputs and outputs of a controlmodule.

FIG. 10 shows a block diagram of the inputs, outputs, and components ofa controller.

FIGS. 11A-11C show various views of a self-propelled autonomous platformuseful for testing the autonomous navigation system of an autonomousvehicle.

FIG. 12 shows a rear facing perspective view of the platform depicted inFIGS. 11A-11C.

FIG. 13 shows a perspective view of a downward facing surface of theplatform depicted in FIGS. 11A-12 .

FIGS. 14A-14B show detailed view of a sensor retraction mechanism in thefirst and second states respectively.

FIGS. 15A-15C show an alternative platform suspension to the suspensiondepicted in FIGS. 11A-14B.

FIG. 16 shows a perspective view of a bottom surface of a platform,which incorporates the alternative suspension depicted in FIG. 15 .

FIG. 17A shows an exemplary testing setup in which an autonomousplatform with a pedestrian target mounted atop it is positioned at theentrance to a cross-walk.

FIG. 17B shows a perspective view of another testing setup in which alaser transmitter and a laser receiver are employed to determine when anautonomous vehicle has reached a predetermined location.

FIGS. 18A-18B show top views of an exemplary intersection testing setupfor an autonomous vehicle with multiple autonomous platforms configuredto execute different movement patterns.

FIG. 19 is a flow chart of an example process for causing aself-propelled platform to follow a first movement route in accordancewith a user input

DETAILED DESCRIPTION

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the present disclosure. It will be apparent, however,that the present disclosure may be practiced without these specificdetails. In other instances, well-known structures and devices are shownin block diagram form in order to avoid unnecessarily obscuring thepresent invention.

In the drawings, specific arrangements or orderings of schematicelements, such as those representing devices, modules, instructionblocks and data elements, are shown for ease of description. However, itshould be understood by those skilled in the art that the specificordering or arrangement of the schematic elements in the drawings is notmeant to imply that a particular order or sequence of processing, orseparation of processes, is required. Further, the inclusion of aschematic element in a drawing is not meant to imply that such elementis required in all embodiments or that the features represented by suchelement may not be included in or combined with other elements in someembodiments.

Further, in the drawings, where connecting elements, such as solid ordashed lines or arrows, are used to illustrate a connection,relationship, or association between or among two or more otherschematic elements, the absence of any such connecting elements is notmeant to imply that no connection, relationship, or association canexist. In other words, some connections, relationships, or associationsbetween elements are not shown in the drawings so as not to obscure thedisclosure. In addition, for ease of illustration, a single connectingelement is used to represent multiple connections, relationships orassociations between elements. For example, where a connecting elementrepresents a communication of signals, data, or instructions, it shouldbe understood by those skilled in the art that such element representsone or multiple signal paths (e.g., a bus), as may be needed, to affectthe communication.

Reference will now be made in detail to embodiments, examples of whichare illustrated in the accompanying drawings. In the following detaileddescription, numerous specific details are set forth in order to providea thorough understanding of the various described embodiments. However,it will be apparent to one of ordinary skill in the art that the variousdescribed embodiments may be practiced without these specific details.In other instances, well-known methods, procedures, components,circuits, and networks have not been described in detail so as not tounnecessarily obscure aspects of the embodiments.

Several features are described hereafter that can each be usedindependently of one another or with any combination of other features.However, any individual feature may not address any of the problemsdiscussed above or might only address one of the problems discussedabove. Some of the problems discussed above might not be fully addressedby any of the features described herein. Although headings are provided,information related to a particular heading, but not found in thesection having that heading, may also be found elsewhere in thisdescription. Embodiments are described herein according to the followingoutline:

-   -   1. General Overview    -   2. Hardware Overview    -   3. Autonomous Vehicle Architecture    -   4. Autonomous Vehicle Inputs    -   5. Autonomous Vehicle Planning    -   6. Autonomous Vehicle Control    -   7. Computing System for Object Detection Using Pillars    -   8. Example Point Clouds and Pillars    -   9. Example Process for Detecting Objects and Operating the        Vehicle Based on the Detection of the Objects

General Overview

Autonomous vehicles driving in complex environments (e.g., an urbanenvironment) pose a great technological challenge. In order forautonomous vehicles to navigate these environments, the vehicles detectvarious types of objects such as vehicles, pedestrians, and bikes inreal-time using sensors such as LIDAR, optical imagery and/or RADAR.While these sensors are able to identify and track objects, predictingthe behavior of the objects can be challenging and treating the trackedobjects too conservatively can result in autonomous vehicles beingunable to function. The disclosed embodiments include a low-profileself-propelled autonomous platform capable of carrying and maneuveringpedestrian, cyclist and/or vehicular type targets while testing one ormore autonomous vehicles.

In particular, the system and techniques described herein enhance theability of testers to comprehensively validate the ability of anautonomous navigation system of an autonomous vehicle to safely navigatea road or intersection. The described platform includes a retractablesensor that allows the platform to track nearby objects and theautonomous vehicle during one or more test runs. The retractable natureof the sensor allows it to be positioned in a location with goodvisibility with minimal risk of damage being done to the sensor in theevent the platform comes into contact with the autonomous vehicle. Theonboard sensor also allows the platform to maneuver relative to dynamicobjects that may not always follow the same path. In this way, theplatform has more flexibility and does not need to be reprogrammed orredirected every time a scenario is adjusted.

Hardware Overview

FIG. 1 shows an example of an autonomous vehicle 100 having autonomouscapability.

As used herein, the term “autonomous capability” refers to a function,feature, or facility that enables a vehicle to be partially or fullyoperated without real-time human intervention, including withoutlimitation fully autonomous vehicles, highly autonomous vehicles, andconditionally autonomous vehicles.

As used herein, an autonomous vehicle (AV) is a vehicle that possessesautonomous capability.

As used herein, “vehicle” includes means of transportation of goods orpeople. For example, cars, buses, trains, airplanes, drones, trucks,boats, ships, submersibles, dirigibles, etc. A driverless car is anexample of a vehicle.

As used herein, “trajectory” refers to a path or route to navigate an AVfrom a first spatiotemporal location to a second spatiotemporallocation. In an embodiment, the first spatiotemporal location isreferred to as the initial or starting location and the secondspatiotemporal location is referred to as the destination, finallocation, goal, goal position, or goal location. In some examples, atrajectory is made up of one or more segments (e.g., sections of road)and each segment is made up of one or more blocks (e.g., portions of alane or intersection). In an embodiment, the spatiotemporal locationscorrespond to real world locations. For example, the spatiotemporallocations are pick up or drop-off locations to pick up or drop-offpersons or goods.

As used herein, “sensor(s)” includes one or more hardware componentsthat detect information about the environment surrounding the sensor.Some of the hardware components can include sensing components (e.g.,image sensors, biometric sensors), transmitting and/or receivingcomponents (e.g., laser or radio frequency wave transmitters andreceivers), electronic components such as analog-to-digital converters,a data storage device (such as a RAM and/or a nonvolatile storage),software or firmware components and data processing components such asan ASIC (application-specific integrated circuit), a microprocessorand/or a microcontroller.

As used herein, a “scene description” is a data structure (e.g., list)or data stream that includes one or more classified or labeled objectsdetected by one or more sensors on the AV vehicle or provided by asource external to the AV.

As used herein, a “road” is a physical area that can be traversed by avehicle, and may correspond to a named thoroughfare (e.g., city street,interstate freeway, etc.) or may correspond to an unnamed thoroughfare(e.g., a driveway in a house or office building, a section of a parkinglot, a section of a vacant lot, a dirt path in a rural area, etc.).Because some vehicles (e.g., 4-wheel-drive pickup trucks, sport utilityvehicles, etc.) are capable of traversing a variety of physical areasnot specifically adapted for vehicle travel, a “road” may be a physicalarea not formally defined as a thoroughfare by any municipality or othergovernmental or administrative body.

As used herein, a “lane” is a portion of a road that can be traversed bya vehicle, and may correspond to most or all of the space between lanemarkings, or may correspond to only some (e.g., less than 50%) of thespace between lane markings. For example, a road having lane markingsspaced far apart might accommodate two or more vehicles between themarkings, such that one vehicle can pass the other without traversingthe lane markings, and thus could be interpreted as having a lanenarrower than the space between the lane markings, or having two lanesbetween the lane markings. A lane could also be interpreted in theabsence of lane markings. For example, a lane may be defined based onphysical features of an environment, e.g., rocks and trees along athoroughfare in a rural area.

“One or more” includes a function being performed by one element, afunction being performed by more than one element, e.g., in adistributed fashion, several functions being performed by one element,several functions being performed by several elements, or anycombination of the above.

It will also be understood that, although the terms first, second, etc.are, in some instances, used herein to describe various elements, theseelements should not be limited by these terms. These terms are only usedto distinguish one element from another. For example, a first contactcould be termed a second contact, and, similarly, a second contact couldbe termed a first contact, without departing from the scope of thevarious described embodiments. The first contact and the second contactare both contacts, but they are not the same contact, unless specifiedotherwise.

The terminology used in the description of the various describedembodiments herein is for the purpose of describing particularembodiments only and is not intended to be limiting. As used in thedescription of the various described embodiments and the appendedclaims, the singular forms “a,” “an” and “the” are intended to includethe plural forms as well, unless the context clearly indicatesotherwise. It will also be understood that the term “and/or” as usedherein refers to and encompasses any and all possible combinations ofone or more of the associated listed items. It will be furtherunderstood that the terms “includes,” “including,” “comprises,” and/or“comprising,” when used in this description, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

As used herein, the term “if” is, optionally, construed to mean “when”or “upon” or “in response to determining” or “in response to detecting,”depending on the context. Similarly, the phrase “if it is determined” or“if [a stated condition or event] is detected” is, optionally, construedto mean “upon determining” or “in response to determining” or “upondetecting [the stated condition or event]” or “in response to detecting[the stated condition or event],” depending on the context.

As used herein, an AV system refers to the AV along with the array ofhardware, software, stored data, and data generated in real-time thatsupports the operation of the AV. In an embodiment, the AV system isincorporated within the AV. In an embodiment, the AV system is spreadacross several locations. For example, some of the software of the AVsystem is implemented on a cloud computing environment similar to cloudcomputing environment 200 described below with respect to FIG. 2 .

In general, this document describes technologies applicable to anyvehicles that have one or more autonomous capabilities including fullyautonomous vehicles, highly autonomous vehicles, and conditionallyautonomous vehicles, such as so-called Level 5, Level 4 and Level 3vehicles, respectively (see SAE International's standard J3016: Taxonomyand Definitions for Terms Related to On-Road Motor Vehicle AutomatedDriving Systems, which is incorporated by reference in its entirety, formore details on the classification of levels of autonomy in vehicles).The technologies described in this document are also applicable topartially autonomous vehicles and driver assisted vehicles, such asso-called Level 2 and Level 1 vehicles (see SAE International's standardJ3016: Taxonomy and Definitions for Terms Related to On-Road MotorVehicle Automated Driving Systems). In an embodiment, one or more of theLevel 1, 2, 3, 4 and 5 vehicle systems may automate certain vehicleoperations (e.g., steering, braking, and using maps) under certainoperating conditions based on processing of sensor inputs. Thetechnologies described in this document can benefit vehicles in anylevels, ranging from fully autonomous vehicles to human-operatedvehicles.

Referring to FIG. 1 , an AV system 120 operates the AV 100 along atrajectory 198 through an environment 190 to a destination 199(sometimes referred to as a final location) while avoiding objects(e.g., natural obstructions 191, vehicles 193, pedestrians 192,cyclists, and other obstacles) and obeying rules of the road (e.g.,rules of operation or driving preferences).

In an embodiment, the AV system 120 includes devices 101 that areinstrumented to receive and act on operational commands from thecomputer processors 146. In an embodiment, computing processors 146 aresimilar to the processor 304 described below in reference to FIG. 3 .Examples of devices 101 include a steering control 102, brakes 103,gears, accelerator pedal or other acceleration control mechanisms,windshield wipers, side-door locks, window controls, andturn-indicators.

In an embodiment, the AV system 120 includes sensors 121 for measuringor inferring properties of state or condition of the AV 100, such as theAV's position, linear and angular velocity and acceleration, and heading(e.g., an orientation of the leading end of AV 100). Example of sensors121 are GPS, inertial measurement units (IMU) that measure both vehiclelinear accelerations and angular rates, wheel speed sensors formeasuring or estimating wheel slip ratios, wheel brake pressure orbraking torque sensors, engine torque or wheel torque sensors, andsteering angle and angular rate sensors.

In an embodiment, the sensors 121 also include sensors for sensing ormeasuring properties of the AV's environment. For example, monocular orstereo video cameras 122 in the visible light, infrared or thermal (orboth) spectra, LiDAR 123, RADAR, ultrasonic sensors, time-of-flight(TOF) depth sensors, speed sensors, temperature sensors, humiditysensors, and precipitation sensors.

In an embodiment, the AV system 120 includes a data storage unit 142 andmemory 144 for storing machine instructions associated with computerprocessors 146 or data collected by sensors 121. In an embodiment, thedata storage unit 142 is similar to the ROM 308 or storage device 310described below in relation to FIG. 3 . In an embodiment, memory 144 issimilar to the main memory 306 described below. In an embodiment, thedata storage unit 142 and memory 144 store historical, real-time, and/orpredictive information about the environment 190. In an embodiment, thestored information includes maps, driving performance, trafficcongestion updates or weather conditions. In an embodiment, datarelating to the environment 190 is transmitted to the AV 100 via acommunications channel from a remotely located database 134.

In an embodiment, the AV system 120 includes communications devices 140for communicating measured or inferred properties of other vehicles'states and conditions, such as positions, linear and angular velocities,linear and angular accelerations, and linear and angular headings to theAV 100. These devices include Vehicle-to-Vehicle (V2V) andVehicle-to-Infrastructure (V2I) communication devices and devices forwireless communications over point-to-point or ad hoc networks or both.In an embodiment, the communications devices 140 communicate across theelectromagnetic spectrum (including radio and optical communications) orother media (e.g., air and acoustic media). A combination ofVehicle-to-Vehicle (V2V) Vehicle-to-Infrastructure (V2I) communication(and, in some embodiments, one or more other types of communication) issometimes referred to as Vehicle-to-Everything (V2X) communication. V2Xcommunication typically conforms to one or more communications standardsfor communication with, between, and among autonomous vehicles.

In an embodiment, the communication devices 140 include communicationinterfaces. For example, wired, wireless, WiMAX, WiFi, Bluetooth,satellite, cellular, optical, near field, infrared, or radio interfaces.The communication interfaces transmit data from a remotely locateddatabase 134 to AV system 120. In an embodiment, the remotely locateddatabase 134 is embedded in a cloud computing environment 200 asdescribed in FIG. 2 . The communication interfaces 140 transmit datacollected from sensors 121 or other data related to the operation of AV100 to the remotely located database 134. In an embodiment,communication interfaces 140 transmit information that relates toteleoperations to the AV 100. In some embodiments, the AV 100communicates with other remote (e.g., “cloud”) servers 136.

In an embodiment, the remotely located database 134 also stores andtransmits digital data (e.g., storing data such as road and streetlocations). Such data is stored on the memory 144 on the AV 100, ortransmitted to the AV 100 via a communications channel from the remotelylocated database 134.

In an embodiment, the remotely located database 134 stores and transmitshistorical information about driving properties (e.g., speed andacceleration profiles) of vehicles that have previously traveled alongtrajectory 198 at similar times of day. In one implementation, such datamay be stored on the memory 144 on the AV 100, or transmitted to the AV100 via a communications channel from the remotely located database 134.

Computing devices 146 located on the AV 100 algorithmically generatecontrol actions based on both real-time sensor data and priorinformation, allowing the AV system 120 to execute its autonomousdriving capabilities.

In an embodiment, the AV system 120 includes computer peripherals 132coupled to computing devices 146 for providing information and alertsto, and receiving input from, a user (e.g., an occupant or a remoteuser) of the AV 100. In an embodiment, peripherals 132 are similar tothe display 312, input device 314, and cursor controller 316 discussedbelow in reference to FIG. 3 . The coupling is wireless or wired. Anytwo or more of the interface devices may be integrated into a singledevice.

In an embodiment, AV system 120 can be incorporated into an autonomousplatform configured to carry a target suitable for testing performanceof sensors of AV 100 and is described and depicted in greater detailbelow in FIGS. 11A-16 . The autonomous platform can be configured withsteering controller 102, brakes 103, communication devices 140 and oneor more processors for receiving and processing instructions in the formof computer code stored on local or remote computer storage. Theautonomous platform can also include one or more sensors 121 that caninclude a LiDAR sensor, a video camera, a GPS receiver and the like. Insome embodiments, one or more of sensors 121 can be used by theautonomous platform to refine a desired position or path taken by theautonomous platform with respect to its environment and or the AV 100 itis being used to test.

FIG. 2 illustrates an example “cloud” computing environment. Cloudcomputing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g., networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services). Intypical cloud computing systems, one or more large cloud data centershouse the machines used to deliver the services provided by the cloud.Referring now to FIG. 2 , the cloud computing environment 200 includescloud data centers 204 a, 204 b, and 204 c that are interconnectedthrough the cloud 202. Data centers 204 a, 204 b, and 204 c providecloud computing services to computer systems 206 a, 206 b, 206 c, 206 d,206 e, and 206 f connected to cloud 202.

The cloud computing environment 200 includes one or more cloud datacenters. In general, a cloud data center, for example the cloud datacenter 204 a shown in FIG. 2 , refers to the physical arrangement ofservers that make up a cloud, for example the cloud 202 shown in FIG. 2, or a particular portion of a cloud. For example, servers arephysically arranged in the cloud datacenter into rooms, groups, rows,and racks. A cloud datacenter has one or more zones, which include oneor more rooms of servers. Each room has one or more rows of servers, andeach row includes one or more racks. Each rack includes one or moreindividual server nodes. In some implementation, servers in zones,rooms, racks, and/or rows are arranged into groups based on physicalinfrastructure requirements of the datacenter facility, which includepower, energy, thermal, heat, and/or other requirements. In anembodiment, the server nodes are similar to the computer systemdescribed in FIG. 3 . The data center 204 a has many computing systemsdistributed through many racks.

The cloud 202 includes cloud data centers 204 a, 204 b, and 204 c alongwith the network and networking resources (for example, networkingequipment, nodes, routers, switches, and networking cables) thatinterconnect the cloud data centers 204 a, 204 b, and 204 c and helpfacilitate the computing systems' 206 a-f access to cloud computingservices. In an embodiment, the network represents any combination ofone or more local networks, wide area networks, or internetworks coupledusing wired or wireless links deployed using terrestrial or satelliteconnections. Data exchanged over the network, is transferred using anynumber of network layer protocols, such as Internet Protocol (IP),Multiprotocol Label Switching (MPLS), Asynchronous Transfer Mode (ATM),Frame Relay, etc. Furthermore, in embodiments where the networkrepresents a combination of multiple sub-networks, different networklayer protocols are used at each of the underlying sub-networks. In someembodiments, the network represents one or more interconnectedinternetworks, such as the public Internet.

The computing systems 206 a-f or cloud computing services consumers areconnected to the cloud 202 through network links and network adapters.In an embodiment, the computing systems 206 a-f are implemented asvarious computing devices, for example servers, desktops, laptops,tablet, smartphones, Internet of Things (IoT) devices, autonomousvehicles (including, cars, drones, shuttles, trains, buses, etc.) andconsumer electronics. In an embodiment, the computing systems 206 a-fare implemented in or as a part of other systems.

FIG. 3 illustrates a computer system 300. In an implementation, thecomputer system 300 is a special purpose computing device. Thespecial-purpose computing device is hard-wired to perform the techniquesor includes digital electronic devices such as one or moreapplication-specific integrated circuits (ASICs) or field programmablegate arrays (FPGAs) that are persistently programmed to perform thetechniques, or may include one or more general purpose hardwareprocessors programmed to perform the techniques pursuant to programinstructions in firmware, memory, other storage, or a combination. Suchspecial-purpose computing devices may also combine custom hard-wiredlogic, ASICs, or FPGAs with custom programming to accomplish thetechniques. In various embodiments, the special-purpose computingdevices are desktop computer systems, portable computer systems,handheld devices, network devices or any other device that incorporateshard-wired and/or program logic to implement the techniques.

In an embodiment, the computer system 300 includes a bus 302 or othercommunication mechanism for communicating information, and a hardwareprocessor 304 coupled with a bus 302 for processing information. Thehardware processor 304 is, for example, a general-purposemicroprocessor. The computer system 300 also includes a main memory 306,such as a random-access memory (RAM) or other dynamic storage device,coupled to the bus 302 for storing information and instructions to beexecuted by processor 304. In one implementation, the main memory 306 isused for storing temporary variables or other intermediate informationduring execution of instructions to be executed by the processor 304.Such instructions, when stored in non-transitory storage mediaaccessible to the processor 304, render the computer system 300 into aspecial-purpose machine that is customized to perform the operationsspecified in the instructions.

In an embodiment, the computer system 300 further includes a read onlymemory (ROM) 308 or other static storage device coupled to the bus 302for storing static information and instructions for the processor 304. Astorage device 310, such as a magnetic disk, optical disk, solid-statedrive, or three-dimensional cross point memory is provided and coupledto the bus 302 for storing information and instructions.

In an embodiment, the computer system 300 is coupled via the bus 302 toa display 312, such as a cathode ray tube (CRT), a liquid crystaldisplay (LCD), plasma display, light emitting diode (LED) display, or anorganic light emitting diode (OLED) display for displaying informationto a computer user. An input device 314, including alphanumeric andother keys, is coupled to bus 302 for communicating information andcommand selections to the processor 304. Another type of user inputdevice is a cursor controller 316, such as a mouse, a trackball, atouch-enabled display, or cursor direction keys for communicatingdirection information and command selections to the processor 304 andfor controlling cursor movement on the display 312. This input devicetypically has two degrees of freedom in two axes, a first axis (e.g.,x-axis) and a second axis (e.g., y-axis), that allows the device tospecify positions in a plane.

According to one embodiment, the techniques herein are performed by thecomputer system 300 in response to the processor 304 executing one ormore sequences of one or more instructions contained in the main memory306. Such instructions are read into the main memory 306 from anotherstorage medium, such as the storage device 310. Execution of thesequences of instructions contained in the main memory 306 causes theprocessor 304 to perform the process steps described herein. Inalternative embodiments, hard-wired circuitry is used in place of or incombination with software instructions.

The term “storage media” as used herein refers to any non-transitorymedia that store data and/or instructions that cause a machine tooperate in a specific fashion. Such storage media includes non-volatilemedia and/or volatile media. Non-volatile media includes, for example,optical disks, magnetic disks, solid-state drives, or three-dimensionalcross point memory, such as the storage device 310. Volatile mediaincludes dynamic memory, such as the main memory 306. Common forms ofstorage media include, for example, a floppy disk, a flexible disk, harddisk, solid-state drive, magnetic tape, or any other magnetic datastorage medium, a CD-ROM, any other optical data storage medium, anyphysical medium with patterns of holes, a RAM, a PROM, and EPROM, aFLASH-EPROM, NV-RAM, or any other memory chip or cartridge.

Storage media is distinct from but may be used in conjunction withtransmission media. Transmission media participates in transferringinformation between storage media. For example, transmission mediaincludes coaxial cables, copper wire and fiber optics, including thewires that comprise the bus 302. Transmission media can also take theform of acoustic or light waves, such as those generated duringradio-wave and infrared data communications.

In an embodiment, various forms of media are involved in carrying one ormore sequences of one or more instructions to the processor 304 forexecution. For example, the instructions are initially carried on amagnetic disk or solid-state drive of a remote computer. The remotecomputer loads the instructions into its dynamic memory and send theinstructions over a telephone line using a modem. A modem local to thecomputer system 300 receives the data on the telephone line and use aninfrared transmitter to convert the data to an infrared signal. Aninfrared detector receives the data carried in the infrared signal andappropriate circuitry places the data on the bus 302. The bus 302carries the data to the main memory 306, from which processor 304retrieves and executes the instructions. The instructions received bythe main memory 306 may optionally be stored on the storage device 310either before or after execution by processor 304.

The computer system 300 also includes a communication interface 318coupled to the bus 302. The communication interface 318 provides atwo-way data communication coupling to a network link 320 that isconnected to a local network 322. For example, the communicationinterface 318 is an integrated service digital network (ISDN) card,cable modem, satellite modem, or a modem to provide a data communicationconnection to a corresponding type of telephone line. As anotherexample, the communication interface 318 is a local area network (LAN)card to provide a data communication connection to a compatible LAN. Insome implementations, wireless links are also implemented. In any suchimplementation, the communication interface 318 sends and receiveselectrical, electromagnetic, or optical signals that carry digital datastreams representing various types of information.

The network link 320 typically provides data communication through oneor more networks to other data devices. For example, the network link320 provides a connection through the local network 322 to a hostcomputer 324 or to a cloud data center or equipment operated by anInternet Service Provider (ISP) 326. The ISP 326 in turn provides datacommunication services through the world-wide packet data communicationnetwork now commonly referred to as the “Internet” 328. The localnetwork 322 and Internet 328 both use electrical, electromagnetic oroptical signals that carry digital data streams. The signals through thevarious networks and the signals on the network link 320 and through thecommunication interface 318, which carry the digital data to and fromthe computer system 300, are example forms of transmission media. In anembodiment, the network 320 contains the cloud 202 or a part of thecloud 202 described above.

The computer system 300 sends messages and receives data, includingprogram code, through the network(s), the network link 320, and thecommunication interface 318. In an embodiment, the computer system 300receives code for processing. The received code is executed by theprocessor 304 as it is received, and/or stored in storage device 310, orother non-volatile storage for later execution.

Autonomous Vehicle Architecture

FIG. 4 shows an example architecture 400 for an autonomous vehicle(e.g., the AV 100 shown in FIG. 1 ). The architecture 400 includes aperception module 402 (sometimes referred to as a perception circuit), aplanning module 404 (sometimes referred to as a planning circuit), acontrol module 406 (sometimes referred to as a control circuit), alocalization module 408 (sometimes referred to as a localizationcircuit), and a database module 410 (sometimes referred to as a databasecircuit). Each module plays a role in the operation of the AV 100.Together, the modules 402, 404, 406, 408, and 410 may be part of the AVsystem 120 shown in FIG. 1 . In some embodiments, any of the modules402, 404, 406, 408, and 410 is a combination of computer software (e.g.,executable code stored on a computer-readable medium) and computerhardware (e.g., one or more microprocessors, microcontrollers,application-specific integrated circuits [ASICs]), hardware memorydevices, other types of integrated circuits, other types of computerhardware, or a combination of any or all of these things).

In use, the planning module 404 receives data representing a destination412 and determines data representing a trajectory 414 (sometimesreferred to as a route) that can be traveled by the AV 100 to reach(e.g., arrive at) the destination 412. In order for the planning module404 to determine the data representing the trajectory 414, the planningmodule 404 receives data from the perception module 402, thelocalization module 408, and the database module 410.

The perception module 402 identifies nearby physical objects using oneor more sensors 121, e.g., as also shown in FIG. 1 . The objects areclassified (e.g., grouped into types such as pedestrian, bicycle,automobile, traffic sign, etc.) and a scene description including theclassified objects 416 is provided to the planning module 404.

The planning module 404 also receives data representing the AV position418 from the localization module 408. The localization module 408determines the AV position by using data from the sensors 121 and datafrom the database module 410 (e.g., a geographic data) to calculate aposition. For example, the localization module 408 uses data from a GNSS(Global Navigation Satellite System) sensor and geographic data tocalculate a longitude and latitude of the AV. In an embodiment, dataused by the localization module 408 includes high-precision maps of theroadway geometric properties, maps describing road network connectivityproperties, maps describing roadway physical properties (such as trafficspeed, traffic volume, the number of vehicular and cyclist trafficlanes, lane width, lane traffic directions, or lane marker types andlocations, or combinations of them), and maps describing the spatiallocations of road features such as crosswalks, traffic signs or othertravel signals of various types.

The control module 406 receives the data representing the trajectory 414and the data representing the AV position 418 and operates the controlfunctions 420 a-c (e.g., steering, throttling, braking, ignition) of theAV in a manner that will cause the AV 100 to travel the trajectory 414to the destination 412. For example, if the trajectory 414 includes aleft turn, the control module 406 will operate the control functions 420a-c in a manner such that the steering angle of the steering functionwill cause the AV 100 to turn left and the throttling and braking willcause the AV 100 to pause and wait for passing pedestrians or vehiclesbefore the turn is made.

Autonomous Vehicle Inputs

FIG. 5 shows an example of inputs 502 a-d (e.g., sensors 121 shown inFIG. 1 ) and outputs 504 a-d (e.g., sensor data) that is used by theperception module 402 (FIG. 4 ). One input 502 a is a LiDAR (LightDetection and Ranging) system (e.g., LiDAR 123 shown in FIG. 1 ). LiDARis a technology that uses light (e.g., bursts of light such as infraredlight) to obtain data about physical objects in its line of sight. ALiDAR system produces LiDAR data as output 504 a. For example, LiDARdata is collections of 3D or 2D points (also known as a point clouds)that are used to construct a representation of the environment 190.

Another input 502 b is a RADAR system. RADAR is a technology that usesradio waves to obtain data about nearby physical objects. RADARs canobtain data about objects not within the line of sight of a LiDARsystem. A RADAR system 502 b produces RADAR data as output 504 b. Forexample, RADAR data are one or more radio frequency electromagneticsignals that are used to construct a representation of the environment190.

Another input 502 c is a camera system. A camera system uses one or morecameras (e.g., digital cameras using a light sensor such as acharge-coupled device [CCD]) to obtain information about nearby physicalobjects. A camera system produces camera data as output 504 c. Cameradata often takes the form of image data (e.g., data in an image dataformat such as RAW, JPEG, PNG, etc.). In some examples, the camerasystem has multiple independent cameras, e.g., for the purpose ofstereopsis (stereo vision), which enables the camera system to perceivedepth. Although the objects perceived by the camera system are describedhere as “nearby,” this is relative to the AV. In use, the camera systemmay be configured to “see” objects far, e.g., up to a kilometer or moreahead of the AV. Accordingly, the camera system may have features suchas sensors and lenses that are optimized for perceiving objects that arefar away.

Another input 502 d is a traffic light detection (TLD) system. A TLDsystem uses one or more cameras to obtain information about trafficlights, street signs, and other physical objects that provide visualnavigation information. A TLD system produces TLD data as output 504 d.TLD data often takes the form of image data (e.g., data in an image dataformat such as RAW, JPEG, PNG, etc.). A TLD system differs from a systemincorporating a camera in that a TLD system uses a camera with a widefield of view (e.g., using a wide-angle lens or a fish-eye lens) inorder to obtain information about as many physical objects providingvisual navigation information as possible, so that the AV 100 has accessto all relevant navigation information provided by these objects. Forexample, the viewing angle of the TLD system may be about 120 degrees ormore.

In some embodiments, outputs 504 a-d are combined using a sensor fusiontechnique. Thus, either the individual outputs 504 a-d are provided toother systems of the AV 100 (e.g., provided to a planning module 404 asshown in FIG. 4 ), or the combined output can be provided to the othersystems, either in the form of a single combined output or multiplecombined outputs of the same type (e.g., using the same combinationtechnique or combining the same outputs or both) or different types type(e.g., using different respective combination techniques or combiningdifferent respective outputs or both). In some embodiments, an earlyfusion technique is used. An early fusion technique is characterized bycombining outputs before one or more data processing steps are appliedto the combined output. In some embodiments, a late fusion technique isused. A late fusion technique is characterized by combining outputsafter one or more data processing steps are applied to the individualoutputs.

FIG. 6 shows an example of a LiDAR system 602 (e.g., the input 502 ashown in FIG. 5 ). The LiDAR system 602 emits light 604 a-c from a lightemitter 606 (e.g., a laser transmitter). Light emitted by a LiDAR systemis typically not in the visible spectrum; for example, infrared light isoften used. Some of the light 604 b emitted encounters a physical object608 (e.g., a vehicle) and reflects back to the LiDAR system 602. (Lightemitted from a LiDAR system typically does not penetrate physicalobjects, e.g., physical objects in solid form.) The LiDAR system 602also has one or more light detectors 610, which detect the reflectedlight. In an embodiment, one or more data processing systems associatedwith the LiDAR system generates an image 612 representing the field ofview 614 of the LiDAR system. The image 612 includes information thatrepresents the boundaries 616 of a physical object 608. In this way, theimage 612 is used to determine the boundaries 616 of one or morephysical objects near an AV.

FIG. 7 shows the LiDAR system 602 in operation. In the scenario shown inthis figure, the AV 100 receives both camera system output 504 c in theform of an image 702 and LiDAR system output 504 a in the form of LiDARdata points 704. In use, the data processing systems of the AV 100compares the image 702 to the data points 704. In particular, a physicalobject 706 identified in the image 702 is also identified among the datapoints 704. In this way, the AV 100 perceives the boundaries of thephysical object based on the contour and density of the data points 704.

FIG. 8 shows the operation of the LiDAR system 602 in additional detail.As described above, the AV 100 detects the boundary of a physical objectbased on characteristics of the data points detected by the LiDAR system602. As shown in FIG. 8 , a flat object, such as the ground 802, willreflect light 804 a-d emitted from a LiDAR system 602 in a consistentmanner. Put another way, because the LiDAR system 602 emits light usingconsistent spacing, the ground 802 will reflect light back to the LiDARsystem 602 with the same consistent spacing. As the AV 100 travels overthe ground 802, the LiDAR system 602 will continue to detect lightreflected by the next valid ground point 806 if nothing is obstructingthe road. However, if an object 808 obstructs the road, light 804 e-femitted by the LiDAR system 602 will be reflected from points 810 a-b ina manner inconsistent with the expected consistent manner. From thisinformation, the AV 100 can determine that the object 808 is present.

Autonomous Vehicle Control

FIG. 9 shows a block diagram 900 of the inputs and outputs of a controlmodule 406 (e.g., as shown in FIG. 4 ). A control module operates inaccordance with a controller 1102 which includes, for example, one ormore processors (e.g., one or more computer processors such asmicroprocessors or microcontrollers or both) similar to processor 304,short-term and/or long-term data storage (e.g., memory random-accessmemory or flash memory or both) similar to main memory 306, ROM 308, andstorage device 310, and instructions stored in memory that carry outoperations of the controller 902 when the instructions are executed(e.g., by the one or more processors).

In an embodiment, the controller 902 receives data representing adesired output 904. The desired output 904 typically includes avelocity, e.g., a speed and a heading. The desired output 904 can bebased on, for example, data received from a planning module 404 (e.g.,as shown in FIG. 4 ). In accordance with the desired output 904, thecontroller 902 produces data usable as a throttle input 906 and asteering input 908. The throttle input 1106 represents the magnitude inwhich to engage the throttle (e.g., acceleration control) of an AV 100,e.g., by engaging the steering pedal, or engaging another throttlecontrol, to achieve the desired output 904. In some examples, thethrottle input 1106 also includes data usable to engage the brake (e.g.,deceleration control) of the AV 100. The steering input 908 represents asteering angle, e.g., the angle at which the steering control (e.g.,steering wheel, steering angle actuator, or other functionality forcontrolling steering angle) of the AV should be positioned to achievethe desired output 904.

In an embodiment, the controller 902 receives feedback that is used inadjusting the inputs provided to the throttle and steering. For example,if the AV 100 encounters a disturbance 910, such as a hill, the measuredspeed 912 of the AV 100 is lowered below the desired output speed. In anembodiment, any measured output 914 is provided to the controller 902 sothat the necessary adjustments are performed, e.g., based on thedifferential 913 between the measured speed and desired output. Themeasured output 914 includes measured position 916, measured velocity918, (including speed and heading), measured acceleration 920, and otheroutputs measurable by sensors of the AV 100.

In an embodiment, information about the disturbance 910 is detected inadvance, e.g., by a sensor such as a camera or LiDAR sensor, andprovided to a predictive feedback module 922. The predictive feedbackmodule 922 then provides information to the controller 902 that thecontroller 902 can use to adjust accordingly. For example, if thesensors of the AV 100 detect (“see”) a hill, this information can beused by the controller 902 to prepare to engage the throttle at theappropriate time to avoid significant deceleration.

FIG. 10 shows a block diagram 1000 of the inputs, outputs, andcomponents of the controller 902. The controller 902 has a speedprofiler 1002 which affects the operation of a throttle/brake controller1004. For example, the speed profiler 1002 instructs the throttle/brakecontroller 1004 to engage acceleration or engage deceleration using thethrottle/brake 1006 depending on, e.g., feedback received by thecontroller 902 and processed by the speed profiler 1002.

The controller 902 also has a lateral tracking controller 1008 whichaffects the operation of a steering controller 1010. For example, thelateral tracking controller 1008 instructs the steering controller 1010to adjust the position of the steering angle actuator 1012 depending on,e.g., feedback received by the controller 902 and processed by thelateral tracking controller 1008.

The controller 902 receives several inputs used to determine how tocontrol the throttle/brake 1006 and steering angle actuator 1012. Aplanning module 404 provides information used by the controller 902, forexample, to choose a heading when the AV 100 begins operation and todetermine which road segment to traverse when the AV 100 reaches anintersection. A localization module 408 provides information to thecontroller 902 describing the current location of the AV 100, forexample, so that the controller 902 can determine if the AV 100 is at alocation expected based on the manner in which the throttle/brake 1006and steering angle actuator 1012 are being controlled. In an embodiment,the controller 902 receives information from other inputs 1014, e.g.,information received from databases, computer networks, etc.

Design of Self-Propelled Autonomous Testing Platform

FIGS. 11A-11C show various views of a self-propelled autonomous platform1100 useful for testing the autonomous navigation system of anautonomous vehicle similar to AV 100. FIG. 11A shows a top view ofplatform 1100. Platform 1100 includes platform housing 1102, which cantake the form of a rigid structure having a sloped periphery 1104 thatallows vehicles to drive over platform 1100 without damaging thevehicles or platform 1100. In some embodiments the sloped periphery canhave a linear incline and in some embodiments sloped periphery 1104 canhave a non-linear incline (e.g., a concave or convex arced inclineand/or the like). A central region of platform housing 1102 can includea flat or sloped support surface 1106 configured to support at least onetarget capable of detection by one or more sensors of AV 100. Whenplatform 1100 includes an optical sensor, support surface 1106 canincludes a sensor cover 1108 that forms a portion of support surface1106 when a vehicle drives over platform 1100. Support surface 1106 alsoincludes magnetic attachment points 1110, which are configured to attachto a target support structure. The target support structure includes abase with a magnet or magnetically attractable material that is able tomagnetically interact and attach to magnetic attachment points 1110. Insome embodiments, magnetic attachment points 1110 can take the form ofmagnetically attractable material that magnetically couples to a magnetthat is incorporated into the base of the target support structure. Oncesecurely attached to one or both of magnetic attachment points 1110, thetarget support structure can be used to keep a target upright and stablewhile platform 1100 moves around.

FIG. 11B shows a cross-sectional view of platform 1100 in a first statein accordance with section line A-A. The first state can also bereferred to as a normal operating state in which platform 1100 remainsuntil platform housing 1102 receives a threshold amount of force. Inthis first state sensor cover 1108 is elevated above support surface1106, which allows sensor 1112 an unobstructed view outside of platformhousing 1102. In some embodiments, sensor 1112 allows platform 1100 toadjust its speed relative to another platform or vehicle during a testbased on data generated by sensor 1112. As depicted, wheels 1114protrude from a downward facing surface of platform housing 1102. Wheels1114 can be driven by one or more motors disposed within platformhousing 1102. FIG. 11B also shows a wheel 1116 associated with sensorretraction mechanism 1118.

FIG. 11C shows a cross-sectional view of platform 1100 in a second statein accordance with section line A-A. The second state can also bereferred to as a stationary state, since platform 1100 is not capable ofpropelling itself in this state. In this second state sensor cover 1108is flush or substantially flush with support surface 1106. Thisretracted position of sensor 1112, prevents sensor 1112 from sustainingdamage in the event a wheel of AV 100 happens to run directly oversensor cover 1108. FIG. 11C also shows how wheels 1114 and wheel 1116retract into platform housing 1102 in the second state. Wheels 1114 andwheel 1116 are kept in the first state by sturdy springs that areconfigured to compress or extend only once a threshold amount of forceis applied to platform housing 1102. This disclosed structure allowsplatform 1100 to have a low-profile of less than about 80 mm in height,which makes the platform more aerodynamic and does not substantiallyincrease the height of targets it carries. In this way, targets havingproportions consistent with normal human or vehicular height can be usedwithout having to adjust their height.

FIG. 12 shows a rear facing perspective view of platform 1100. Inparticular, a target support structure 1202 taking the form of acylindrical beam is shown attached to a rear magnetic attachment pointof platform housing 1102. On account of the coupling between targetsupport structure 1202 being magnetically coupled to platform housing1102, in the event a target attached to target support structure 1402 ishit by AV 100, both the target and target support structure 1202 candetach easily from platform housing 1102 without doing substantialdamage to platform 1100 or AV 100. It should be appreciated that targetsupport structure 1402 can take different forms. For example, targetsupport structure 1402 could have target attachment features that allowtarget support structure to be securely attached to a target, therebypreventing inadvertent detachment of the target from platform 1100.

FIG. 13 shows a perspective view of a downward facing surface ofplatform 1100. Target 1302 is shown attached to an upward facing surfaceof platform 1100. In some embodiments, target 1302 can be attacheddirectly to one of the magnetic attachment points of platform housing1102. It should be noted that while target 1302 is depicted as apedestrian in FIG. 13 , platform 1100 is capable of carrying other typesof targets, such as person atop a bike or in cooperation with otherplatforms carry inflatable vehicle shaped targets.

FIG. 13 also shows a close up view 1304 of the downward facing surfaceof platform 1100 where platform 1100 is in the second state. Asdepicted, an interior of platform housing 1102 is substantially hollowallowing room for wheels 1104 and 1106 to retract between structuralribs 1304. Structural ribs 1306 help to keep platform housing 1102 rigidenough to structurally support the passage of AV 100 over platformhousing 1102. Wheel assemblies attaching wheels 1114 to platform housing1102 are attached by pins to one or more of structural ribs 1304. FIG.13 also shows motors 1308, which are in axial alignment with wheels1104-1 and 1104-2. In some embodiments, motors 1308 can be configured tomove with wheels 1104 when platform 1100 changes from the second stateto the first state to maintain the alignment of motors 1308 with wheels1104. Having two motors 1308 allows platform 1100 to perform turns byapplying differential inputs to motors 1308, thereby allowing platform1100 to make left and right turns. The differential inputs can take manyforms including differential power, control signals, electrical current,etc.

FIGS. 14A-14B show detailed view of sensor retraction mechanism 1118 inthe first and second states respectively. FIG. 14A shows sensor 1112protruding above support surface 1106. Sensor 1112 is mechanicallycoupled to wheel 1116 by way of linkage 1402, wheel support 1404 andaxle 1406. While wheel support 1404 and linkage 1402 are shown as twodifferent pieces, in some embodiments, these two pieces could becombined into a single piece. Wheel 1116 is kept in the positiondepicted in FIG. 14A by spring 1408. A first end of spring 1408 issecured to sensor retraction mechanism body 1410 and a second end ofspring 1408 is secured to linkage 1402 at pin 1412. Spring 1408 isconfigured to prevent linkage 1402 from rotating about an axis definedby pin 1414 until a threshold amount of force is applied to platformhousing 1102 at which point spring 1408 is configured to lengthen,thereby allowing linkage 1402 to rotate.

FIG. 14B shows a position of sensor retraction mechanism 1118 whenplatform 1100 is in the second state. Linkage 1402 is shown in a newposition after spring 1408 lengthens to accommodate rotation of linkage1402. Rotation of linkage 1402 results in the retraction of wheel 1116into platform housing 1102 (not shown) and the retraction of sensor 1112into platform housing 1102. Sensor 1112 retracts into platform housing1102 and sensor retraction body 1410 on account of a distal end of 1402pushing pin 1416 downward. Since pin 1416 is coupled to sensor 1112,sensor 1112 is retracted into platform housing 1112 as depicted.

FIGS. 15A-15C show an alternative platform suspension. FIG. 15A shows aperspective view of platform suspension 1500. While platform 1100 has asuspension that includes individual springs for controlling the movementof each wheel, suspension 1500 includes a single chassis 1502 made ofrigid material that attaches each of wheels 1504 to a platform housing.In this way, as the platform moves between a normal operating state anda stationary state, wheels 1504 all move together with chassis 1502.FIG. 15A also shows how motors 1506 are coupled to chassis 1502. Sinceboth motors 1506 and wheels 1504 are attached to the chassis 1502,alignment between motors 1506 and wheels 1504 remains constantregardless of state. Motors 1506 engage wheels 1504 by way of bevelgearing 1508. Alternatively, suspension 1500 could be widened and driveshafts of motors 1506 could be aligned directly with the axes ofrotation of the wheels similar to the configuration shown in FIG. 13 .

Chassis 1502 is also coupled to housing brackets 1510 by multiplesprings 1512 and linkages 1514. Springs 1512 prevent movement of chassis1502 relative to housing brackets 1510 until a threshold amount of forceis applied to them through a respective platform housing. Once springs1512 begin to a stretch under the applied force, linkages 1514 areconfigured to control movement of chassis 1502 with respect to housingbrackets 1510. Because housing brackets 1510 are both rigidly coupled toa respective platform housing, linkages 1514 also control the movementof chassis 1502 with respect to the respective platform housing.

FIGS. 15B and 15C show side views of suspension 1500 in normal andstationary states. The figures demonstrate how chassis 1502 moves upwardand laterally with respect to housing brackets 1510 to facilitateretraction of chassis 1502 into the respective platform housing assprings 1512 extend. FIG. 15C also shows how wheels 1504 retract to anextent that they become even with a base of housing bracket 1510. Insome embodiments, linkages 1514 can be configured such that wheels 1504retract above the base of housing bracket 1510.

FIG. 16 shows a perspective view of a bottom surface of platform 1600,which incorporates the alternative suspension 1500 depicted in FIGS.15A-15C. As depicted, platform 1600 includes a platform housing 1602that defines a series of structural ribs 1604 that span a periphery ofplatform housing 1602. In the peripheral region structural ribs 1604 arearranged in a grid pattern. In a central region of platform housing 1602structural ribs 1606 only run in a single direction and are broken up toallow space to attach suspension 1500 within the central region.

FIG. 17A shows an exemplary testing setup in which an autonomousplatform 1702 with a pedestrian target mounted atop it is positioned atthe entrance to a cross-walk 1704. When AV 100 reaches a predeterminedposition 1706, autonomous platform 1702 can be configured to traversecross-walk 1704. Arrival of AV 100 at position 1706 can be determined ina number of ways. For example, a sensor can be embedded within the roadat position 1706 and configured to identify passage of AV 100. In someembodiments, the sensor can be an RFID reader configured to emit anelectromagnetic field to sense passage of an RFID tag secured to aforward portion of AV 100. The RFID reader can then transmit a signal toautonomous platform 1702 relaying that AV 100 has arrived at position1706. In some embodiments, an on-board optical sensor can be used todetermine when AV 100 has arrived at position 1706. The optical sensorcan be configured to measure the size of a target or feature positionedon an exterior surface of AV 100, allowing analysis of the imagery toprovide distance information. The optical sensor can also be configuredto determine distance from AV 100 by measuring a distance betweenfeatures separated by a known distance.

A path taken by autonomous platform 1702 can be a constant speedstraight path or it can vary substantially. In some embodiments the pathtaken by autonomous platform 1702 can be based on a manual orprogrammatic input. For example, a test manager can manually inputdirectional commands that cause autonomous platform 1702 to do astraight traversal across cross-walk 1704 or a more meandering path thatcan vary in direction and speed while staying within the bounds ofcross-walk 1704.

Regardless of the type of input provided to autonomous platform 1702, itis important that autonomous platform 1702 is able to repeat the sameset of movements so that improvements to the autonomous management of AV100 can be tracked in the event AV 100 is struggling with a particularscenario. Autonomous platform 1702 can perform the movements multipletimes by recording instructions and/or a series of positions it occupiesduring a particular test run. This can allow for the movements to berepeated with precision. It can also be desirable for autonomousplatform 1702 to have the capability to make adjustments ormodifications to a previous set of input commands. This may be helpfulwhere AV 100 performs perfectly to the traversal of autonomous platform1702 across cross-walk 1704, as it allows testers to see if specificchanges to the movement of autonomous platform 1702 across cross-walk1704 causes a failure in the performance of AV 100. For example,autonomous platform can be configured to make controlled adjustments inspeed and/or direction to ensure AV 100 is able to react accordingly toa wide variety of scenarios. In addition to providing a large number ofcontrolled scenario variations, these autonomous adjustments also helpreduce the amount of time needed by individuals to set up the scenariosas one doesn't need to have a dedicated worker driving every autonomousplatform 1702.

FIG. 17B shows a perspective view of another testing setup in which alaser transmitter 1710 and laser receiver 1712 are employed to determinewhen AV 100 has reached a predetermined location. The use of a laserdetection system may provide a quicker response than an RFID reader as asignal can be transmitted as soon as AV 100 disrupts laser receiver 1712from receiving the laser transmitted by laser transmitter 1710. In someembodiments, the laser detection system can also be configured totransmit the speed of AV 100 at the predetermined location by measuringhow long the laser is blocked. The speed of AV 100 at the predeterminedlocation may also be used to determine when autonomous platform 1702begins movement and/or at what speed the movement is carried out. Thiscould be useful in a case a driver was maneuvering AV 100 at differentspeeds and performance of the anti-collision system necessitatesautonomous platform 1702 being positioned for a collision with a frontof AV 100. In some embodiments, an onboard sensor of autonomous platform1702 may be used to assist in positioning autonomous platform 1702 in aparticular position relative to AV 100 at a time of contact. Forexample, while initial movement and direction of autonomous platform1702 can be made in accordance with detection of AV 100 at apredetermined position, one or more sensors such as a LiDAR, RADAR orImagery Sensor can be used to provide cuing to autonomous platform 1702so it is positioned as intended prior to its closest point of approachto AV 100.

FIG. 18A shows a top view of an exemplary intersection testing setup1800 for AV 100 with multiple autonomous platforms 1802-1808 configuredto execute different movement patterns. Autonomous platforms 1802-1808can be configured to execute their movement patterns in response to AV100 arriving at a singular predetermined location or autonomousplatforms 1802 can be configured to execute movement platforms inresponse to AV 100 arriving at different predetermined positions. Forexample, when AV 100 arrives at position 1810, autonomous platforms 1804and 1806 can be configured to traverse crosswalk 1812 and when AV 100reaches position 1814 autonomous platforms 1802 and 1808 traversecrosswalks 1816 and 1818 respectively. In some embodiments, based on aposition and/or speed of platform 1802 within crosswalk 1816 detected byone or more sensors of AV 100, AV 100 may decide to slow down or stopprior to making a right turn crossing through crosswalk 1816. In someembodiments, autonomous platforms 1802-1808 can be configured to augmentreadings from its position sensor or sensors by using an onboard sensorto determine a position of

FIG. 18B shows a top view of testing setup 1800 with autonomousplatforms 1802-1808 cooperating to carry vehicular target 1850 that cantake the form of an inflatable vehicular target. Autonomous platforms1802-1808 can be configured to maintain a formation to carry a largetarget such as vehicular target 1850. Sensors aboard autonomousplatforms 1802 can be configured to help maintain the relativepositioning of autonomous platforms 1802-1808. In some embodiments, oneof autonomous platforms 1802-1808 can be configured to guide motion ofvehicular target 1850 and the other autonomous platforms are configuredto follow changes in direction in speed of the one autonomous platformbased solely upon feedback from onboard sensors or alternatively beconfigured to receive wireless control signals from the controllingautonomous platform and/or cuing from onboard sensors. In someembodiments, vehicular target 1850 can be magnetically coupled to only asingle one of autonomous platforms 1802-1808. This configuration allowsfor easier detachment of vehicular target from the autonomous platformsin the event of a collision.

Autonomous platforms 1802-1808 can be further configured to adjust theiroperation in response to AV 100 arriving at positions 1810 and 1814. Forexample, autonomous platforms 1802-1808 can be configured to slow downin response to AV 100 arriving at position 1810 and come to a completestop when AV 100 arrives at position 1814.

Example Process for Controlling a Self-Propelled Platform

FIG. 19 is a flow chart of an example process 1900 for controlling aself-propelled platform. At 1902 a processor of the self-propelledplatform causes the self-propelled platform to move based on a firstmovement route in accordance with a user input (e.g., a user inputreceived by the processor). In some embodiments, the processor can beconfigured to supply inputs to motors powering the self-propelledplatform to effectuate movement and maneuver of the self-propelledplatform based on the first movement route. The self-propelled platformcan be constructed in accordance with any of the descriptions found inFIGS. 11A-16 . In some embodiments, the user input can be received bythe self-propelled platform prior to execution of the movement andstored in local or cloud-based computer storage as a subroutine thatincludes a desired direction and rate of movement of the self-propelledplatform. The user input could alternatively be input by a remote inputcontrol, allowing an individual controlling the self-propelled platformwith the remote input control to specify a specific path relative to thesurroundings of the self-propelled platform in real-time.

At 1904, during movement of the self-propelled platform, positions ofthe self-propelled platform at particular times or at particularvelocities are recorded in computer memory as a movement route. Theposition information can be recorded in a number of different referenceframes. For example, it may be desirable for the self-propelled platformto always traverse the same portion of a testing setup. Alternatively,it may be more advantageous for the movement to be based entirely or atleast in part upon movement of the self-propelled platform relative to aself-propelled vehicle undergoing testing. The position data can beobtained from one or more systems aboard the self-propelled platformincluding, e.g., a satellite navigation system and an optical or RADARsensor. On-board sensors capable of providing data about objectssurrounding the self-propelled platform are useful in recording thefirst movement route with respect to one or more other self-propelledvehicles.

At 1906, the self-propelled vehicle can be configured to follow a secondmovement route based on the recorded positions of the self-propelledvehicle during the first movement route. In some embodiments, the secondmovement route can be exactly the same or as close to exactly the sameas the first movement route as possible given the accuracy of therecorded positions.

In the foregoing description, embodiments of the invention have beendescribed with reference to numerous specific details that may vary fromimplementation to implementation. The description and drawings are,accordingly, to be regarded in an illustrative rather than a restrictivesense. The sole and exclusive indicator of the scope of the invention,and what is intended by the applicants to be the scope of the invention,is the literal and equivalent scope of the set of claims that issue fromthis application, in the specific form in which such claims issue,including any subsequent correction. Any definitions expressly set forthherein for terms contained in such claims shall govern the meaning ofsuch terms as used in the claims. In addition, when we use the term“further comprising,” in the foregoing description or following claims,what follows this phrase can be an additional step or entity, or asub-step/sub-entity of a previously-recited step or entity.

1. A self-propelled platform, comprising: a plurality of wheels; a motorconfigured to drive at least one of the plurality of wheels; a platformhousing comprising a support surface configured to carry at least onetarget and a sloped periphery configured to accommodate passage of anautonomous vehicle over the platform housing; and a suspensioncomprising a plurality of springs coupling the plurality of wheels tothe platform housing, the plurality of springs configured to transitionthe platform from a first state to a second state in response to athreshold amount of weight being applied to the platform housing,wherein the platform housing is lower in the second state than it is inthe first state.
 2. The self-propelled platform of claim 1, furthercomprising a retractable sensor, wherein the retractable sensorprotrudes from the platform housing when the suspension is in the firststate and is retracted within the platform housing when the suspensionis in the second state.
 3. The self-propelled platform of claim 2,wherein the retractable sensor is mechanically coupled to one of theplurality of wheels by a spring and at least one linkage.
 4. Theself-propelled platform of claim 2, wherein the retractable sensorcomprises an optical sensor.
 5. The self-propelled platform of claim 2,wherein the retractable sensor comprises a LiDAR sensor.
 6. Theself-propelled platform of claim 2, wherein the retractable sensor is afirst retractable sensor and the self-propelled platform furthercomprises a second retractable sensor facing in a different directionthan the first retractable sensor.
 7. The self-propelled platform ofclaim 2, further comprising a motor configured to transition theretractable sensor between the protruding position and the retractedposition based on a determined proximity of the autonomous vehicle tothe self-propelled platform.
 8. The self-propelled platform of claim 1,wherein the sloped periphery of the platform housing and the pluralityof wheels are in direct contact with a surface upon which theself-propelled platform rests when the self-propelled platform is in thesecond state.
 9. The self-propelled platform of claim 1, wherein thesuspension comprises a rigid chassis coupled to each wheel of theplurality of wheels, wherein the chassis is coupled to the platformhousing by the plurality of springs.
 10. The self-propelled platform ofclaim 1, wherein a first wheel of the plurality of wheels is coupled tothe platform housing by a first spring of the plurality of springs and asecond wheel of the plurality of wheels is coupled to the platformhousing by a second spring of the plurality of springs.
 11. Theself-propelled platform of claim 1, wherein the threshold amount ofweight is between 25 kg and 75 kg.
 12. The self-propelled platform ofclaim 1, further comprising a weight on wheels sensor configured todistinguish between the first state and the second state, wherein themotor is configured to cease operation in response to sensor data fromthe weight on wheels sensor indicating the self-propelled platform is inthe second state.
 13. The self-propelled platform of claim 1, whereinthe motor is a first motor and the self-propelled platform furthercomprises a second motor configured to drive a second wheel of theplurality of wheels, wherein the first motor is configured to drive afirst wheel of the plurality of wheels independent from the secondmotor.
 14. The self-propelled platform of claim 13, wherein a drive axisof the first motor is aligned with an axis of rotation of a first wheelof the plurality of wheels.
 15. The self-propelled platform of claim 1,wherein in the first state the self-propelled platform has an overallheight of less than 8 cm.
 16. The self-propelled platform of claim 1,wherein an outside surface of the platform housing comprises at leastone permanent magnet configured to secure a target with a magneticallyattractable plate or magnet to the platform housing.
 17. Theself-propelled platform of claim 16, wherein the target is shaped tosimulate a pedestrian or cyclist.
 18. The self-propelled platform ofclaim 1, further comprising a wireless communication module configuredto receive commands that change a movement route of the self-propelledplatform.
 19. The self-propelled platform of claim 1, furthercomprising: a retractable sensor, wherein the retractable sensorprotrudes from the platform housing when the suspension is in the firststate and is retracted within the platform housing when the suspensionis in the second state; a motor configured to transition the retractablesensor between the protruding position and the retracted position; and awireless communication module configured to receive commands that directthe motor to transition the retractable sensor between the protrudingand retracted positions. 20-39. (canceled)